Enterprise AI Engineering Methodology
Esaholic executes a strict 7-step engineering sequence to build, validate, and deploy production artificial intelligence systems. Sequence carries information: skipping architecture or security hardening leads to production hallucination, cost overruns, and compliance failures.
Sequential Delivery Framework
7 Numbered PhasesDefine performance SLAs, data boundaries, model selection, and security requirements before writing code.
Build layout-aware OCR parsers, chunking strategies, and HNSW vector index pipelines.
Evaluate open-weights models versus proprietary APIs and execute LoRA fine-tuning for domain jargon.
Build LangGraph state machines, MCP server connectors, and Human-in-the-Loop authorization gates.
Deploy NeMo Guardrails, zero data retention API endpoints, and dual-LLM prompt injection classifiers.
Tune vLLM PagedAttention KV cache, AWQ quantization, and semantic response caching.
Deploy Kubernetes microservices, Prometheus telemetry, and automated regression evaluations.
Ready to Initiate Step 1?
Book an architecture discovery session to define technical requirements, latency SLAs, and fixed-scope deliverables.
Initiate Step 1 Discovery Session